At this years IMFAR autism science conference I saw several presentations on seemingly obvious topics. For example, one study (DaPaz, University of California at San Francisco) assessed the responses of 89 parents to their children’s autism. The comments were grouped into three categories – despair/hopelessness; self-blame/searching; and acceptance/benefit finding. The researchers drew conclusions about the relationship between the types of comments and the parent’s states of mind. Not surprisingly the parents who reported mostly despair had poorer outcomes and acceptance was associated with lower stress. When I mentioned that study the most common reaction was, “Isn’t that obvious? Why are we spending money on a study like that?”
There were plenty of other similarly “obvious” studies. For example, one showed that parents who are educated about their children’s autism do better. Another found that kids do better when parents are taught basic autism therapy skills.
Here’s a really important point to consider when you ask why agencies fund studies like that: When it comes to arguing what health insurance should cover, decisions are driven by evidence. You may think a certain thing is obvious, but without clear evidence, you are unlikely to see any insurance company cover it. Even when we think the evidence is clear, doubt may remain and that can necessitate more studies. Occasionally, studies of the obvious reveal really surprising things, showing us that the obvious is sometimes badly misunderstood.
For example we have all hear that employment statistics for autistic people are dismal. “90% unemployed,” is a number that’s commonly bandied about. Personally I always doubted that and in fact an Autistica UK study that I saw on Friday night showed the number was closer to 60%. In that case far more people seem to be working that previously assumed.
There are obvious implications for public health policy in number like that.
There’s a third group of “obvious” studies that we need very much. Those are the studies that further validate initial research results. It’s great when a lab reports positive outcomes for a new intervention or therapy. But one great result is not enough to put that new there app on the menu all across the country. We need a plethora of studies – on disparate populations; done by different groups of researchers – to build a really solid base of evidence that something worked. That’s what it takes to win insurance approval for anything new, and even then, it takes years.
You can certainly decry this system as unfair and exclusionary. You might feel the insurers are just trying to escape what you see as a moral obligation. But of course they would answer that they have responsibilities to both their insured population and their share holders. The fact is, without evidence, we are nowhere with even the best new therapy.
Sometimes these “obvious” studies are conducted by young scientists who are just starting out. I encourage that. Other times they are conducted by better established scientists under the sponsorship of someone with a stake in the therapy under test. We have to be careful with work like that because conflicts of interest can destroy the credibility of even the best done research.
The next time you see a piece of work you think is obvious, rather than criticize it as wasteful, as if this will be enough to expand the coverage of autism services to be closer to what we really need. In far too much of the country, the only thing insurers cover is ABA. That is equivalent to saying the only thing we will cover to treat your depression is Trazodone. All those other depression mess and therapies – not enough evidence for them. How well do you think that would work? If you say, not well at all, that is the reality we face in deploying therapies for autism right now.
That said, we do sometimes have too many studies of certain topics. That is particularly true of well-studied paths that are not direct tests of new therapies. People sometimes ask how many eye tracking studies we need, or how many baby sibs studies? In my opinion, those questions relate to a larger question – the balance of research funding. Should we spend less on basic research (such as the examples I cite) and move some of that money to develop and prove out therapies we could use tomorrow? If my conversations in the community are a guide many who live with autism would say yes, though most would also want basic scientific research to continue.
Deciding how to spend our limited research dollars is difficult. But there’s less outright waste than many people imagine. There is good reason to “master the obvious.”